Why Companies Must Value Their AI the Same Way They Value Their Data

Enterprises have long understood that proprietary data represents a crucial competitive advantage. In response, strong organizations have built muscle to capture and analyze data, and create data-driven cultures. In the AI age, winning organizations must view their AI similarly. It won't be enough to consume out of the box AI point solutions. Companies must develop proprietary AI capabilities in-house to gain a lead and build meaningful moats.
Charlie Basil
Charlie Basil
November 12, 2024

The Power of Proprietary Data

Enterprise organizations have spent decades building valuable data assets that capture their unique customer interactions and preferences, operational processes and efficiencies, market insights and trends, industry-specific knowledge, historical decision-making patterns, and much more.

It took work and fortitude to capture data, wrangle it, analyze it, and become data driven. For those who remained committed, and were able to execute, proprietary data has created a moat that competitors cannot easily replicate. It contains the contextual intelligence and institutional knowledge that makes an organization uniquely positioned to capture advantage.

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The Need For Custom AI Solutions

Proprietary data sets fed into point solutions will get you halfway there. There's a window to get ahead if you're able to navigate the risks, maintain data privacy, and adopt AI now. But that lead will erode over time as point solutions become ubiquitous tools for everyday work.

To become and remain an industry leader, your teams will need to collaborate closely to build custom AI solutions. True competitive advantage in the AI era will come from building bespoke solutions that uniquely combine your proprietary data with custom AI capabilities.

This approach:

  1. Creates Unique Value
    • Integrates your proprietary data directly into AI decision-making
    • Reflects your specific business processes and requirements
    • Delivers insights competitors cannot easily replicate
  2. Builds Institutional Knowledge
    • Captures and operationalizes your organization's expertise
    • Fine tunes AI models that understand your specific context
    • Develops solutions that evolve with your business
  3. Unifies Cross-functional Teams
    • Brings together technical experts, domain experts, and business leaders
    • Ensures AI solutions are tightly aligned with organizational goals and needs
    • Facilitates continuous improvement and innovation
  4. Establishes Competitive Moats
    • Develops unique intellectual property
    • Delivers capabilities not easily replicated by others
    • Continually improves and compounds advantage over time via feedback loops

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The Role of AI Development Platforms

Building custom AI solutions has traditionally been challenging, requiring significant technical expertise and resources. However, modern AI development platforms are changing this paradigm. Tools like Salt that enable technical builders to work full-code and non-technical domain experts to interact with a visual drag and drop interface, are becoming essential for organizations that want to:

  1. Accelerate Development
    • Reduce the technical barriers to custom AI development
    • Enable rapid prototyping and iteration
    • Maintain pace with rapid AI innovation
  2. Maintain Control
    • Keep sensitive data within your organization
    • Customize solutions to exact specifications
    • Own your AI intellectual property
  3. Scale Effectively
    • Deploy solutions across the enterprise
    • Integrate with existing systems and processes
    • Adapt to changing business needs

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The Path Forward

Well-led organizations will view their AI strategy as a capability that must be developed, rather than a suite of solutions to adopt. Just as companies invest in protecting and leveraging their proprietary data, they must now invest in building custom AI solutions that can uniquely exploit that data, expand capabilities, and accelerate growth.

Generic, off-the-shelf AI tools, while useful, will not provide sustainable differentiation. Companies must invest in building unique AI capabilities with the same vigor they've applied to building their data assets.

The organizations that understand this shift—and act on it—will be the ones that thrive in the AI-driven future.

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